EmbeddingGemma 2: an open, lightweight multimodal embedding model blog.google

Google DeepMind researchers Sahil Dua and Henrique Schechter Vera announced EmbeddingGemma 2, a 740-million-parameter model that embeds text, code, images, video and audio in a shared space for on-device search and retrieval. Released under the Apache 2.0 license, it supports an 8K-token context and can use as little as 191MB of active RAM for text-only inference; Google says its code benchmark score rose from 68.76 to 78.68 compared with the first EmbeddingGemma.